Data Quality & AI Validation Analyst

Hire Feed; Argentina; Presencial; ARS 600.000 - 1.200.000; Jornada completa

Descripción de la vacante

Hire Feed is seeking a Human Data Manager, New Grad to join our client’s team on a full-time basis in Argentina. You will ensure the accuracy and integrity of data used in AI and machine learning models by performing quality checks, correcting errors, and validating outputs.

You will collaborate with cross-functional teams to maintain high standards for datasets powering automated systems, perform manual reviews, annotate data, and document issues for transparency and continuous improvement.

Formación

• Bachelor’s degree in Computer Science, Data Science, or related field.
• Experience with data annotation, labeling, or QA processes.
• Experience with spreadsheets, databases, or data visualization tools.
• Strong attention to detail and ability to spot discrepancies in large datasets.
• Proficiency in written and verbal communication for reporting issues and solutions.

Responsabilidades

• Perform manual reviews of AI-generated data to identify inaccuracies, inconsistencies, or biases
• Correct and annotate data points to improve model performance and reliability
• Validate datasets against predefined quality criteria and business requirements
• Document data issues and resolutions for future reference and team transparency
• Communicate findings and recommendations to engineering and product teams

Conocimientos

Data annotation

Quality assurance

Data visualization

Attention to detail

Written and verbal communication

Educación

Bachelor’s degree in Computer Science, Data Science, or related field

Herramientas

Spreadsheets

Databases

Data Visualization Tools

Descripción del empleo

Hire Feed is seeking a Human Data Manager, New Grad to join our client’s team on a full-time basis in Argentina. You will ensure the accuracy and integrity of data used in AI and machine learning models by performing quality checks, correcting errors, and validating outputs.

You will collaborate with cross-functional teams to maintain high standards for datasets powering automated systems, perform manual reviews, annotate data, and document issues for transparency and continuous improvement.